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ICPR
2004
IEEE
14 years 11 months ago
Two-Stage Classification System combining Model-Based and Discriminative Approaches
For the tasks of classification, two types of patterns can generate problems: ambiguous patterns and outliers. Furthermore, it is possible to separate classification algorithms in...
Jonathan Milgram, Mohamed Cheriet, Robert Sabourin
IEEEICCI
2003
IEEE
14 years 3 months ago
Signal Classification through Multifractal Analysis and Complex Domain Neural Networks
This paper describes a system capable of classifying stochastic, self-affine, nonstationary signals produced by nonlinear systems. The classification and analysis of these signals...
Witold Kinsner, V. Cheung, K. Cannons, J. Pear, T....
ACSC
2005
IEEE
14 years 3 months ago
The Electronic Primaries: Predicting the U.S. Presidency Using Feature Selection with Safe Data Reduction
The data mining inspired problem of finding the critical, and most useful features to be used to classify a data set, and construct rules to predict the class of future examples ...
Pablo Moscato, Luke Mathieson, Alexandre Mendes, R...
JMLR
2008
133views more  JMLR 2008»
13 years 10 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
ICMLA
2010
13 years 8 months ago
An All-at-once Unimodal SVM Approach for Ordinal Classification
Abstract--Support vector machines (SVMs) were initially proposed to solve problems with two classes. Despite the myriad of schemes for multiclassification with SVMs proposed since ...
Joaquim F. Pinto da Costa, Ricardo Sousa, Jaime S....